Effect of distance from road intersection on developed traffic noise levels
Bibliographic record
Abstract
The main objective of this study was to evaluate the variation in traffic equivalent noise levels as distance from the road intersection increases. To achieve this objective, traffic volume and equivalent noise level were monitored at 40 signalized intersections in Amman, the capital of Jordan. An integrated sound level meter (ISLM) was used to measure 1 min equivalent noise level along all approaches of the evaluated intersections. A total of 3326 noise measurements were performed. The collected data were analyzed to evaluate the variation of noise levels as distance from the intersection increases. The results indicated that equivalent noise levels were significantly affected by distance from the signal stop line. The equivalent noise levels at distances 50 and 100 m from the intersection were found to be 1.5 to 2.0 dB less than those at 0 m. While at 200, 250, and 300 m from the intersection, the monitored equivalent noise levels were found to be 3.8 to 4 dB higher than that at 0 m. At distances farther than 250 m, the measured equivalent noise levels tend to keep constant value of equivalent noise level as distance increased.Key words: noise, traffic, intersection, environment, pollution.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".